@article{HerzbergMeyerWeske2015,
  author    = {Herzberg, Nico and Meyer, Andreas and Weske, Mathias},
  title     = {Improving business process intelligence by observing object state transitions},
  series = {Data \& knowledge engineering},
  volume    = {98},
  journal   = {Data \& knowledge engineering},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0169-023X},
  doi       = {10.1016/j.datak.2015.07.008},
  pages     = {144 -- 164},
  year      = {2015},
  abstract  = {During the execution of business processes several events happen that are recorded in the company's information systems. These events deliver insights into process executions so that process monitoring and analysis can be performed resulting, for instance, in prediction of upcoming process steps or the analysis of the run time of single steps. While event capturing is trivial when a process engine with integrated logging capabilities is used, manual process execution environments do not provide automatic logging of events, so that typically external devices, like bar code scanners, have to be used. As experience shows, these manual steps are error-prone and induce additional work. Therefore, we use object state transitions as additional monitoring information, so-called object state transition events. Based on these object state transition events, we reason about the enablement and termination of activities and provide the basis for process monitoring and analysis in terms of a large event log. In this paper, we present the concept to utilize information from these object state transition events for capturing process progress. Furthermore, we discuss a methodology to create the required design time artifacts that then are used for monitoring at run time. In a proof-of-concept implementation, we show how the design time and run time side work and prove applicability of the introduced concept of object state transition events. (C) 2015 Elsevier B.V. All rights reserved.},
  language  = {en}
}
@article{MeyerPufahlBatoulisetal.2015,
  author    = {Meyer, Andreas and Pufahl, Luise and Batoulis, Kimon and Fahland, Dirk and Weske, Mathias},
  title     = {Automating data exchange in process choreographies},
  series = {Information systems},
  volume    = {53},
  journal   = {Information systems},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0306-4379},
  doi       = {10.1016/j.is.2015.03.008},
  pages     = {296 -- 329},
  year      = {2015},
  abstract  = {Communication between organizations is formalized as process choreographies in daily business. While the correct ordering of exchanged messages can be modeled and enacted with current choreography techniques, no approach exists to describe and automate the exchange of data between processes in a choreography using messages. This paper describes an entirely model-driven approach for BPMN introducing a few concepts that suffice to model data retrieval, data transformation, message exchange, and correlation four aspects of data exchange. For automation, this work utilizes a recent concept to enact data dependencies in internal processes. We present a modeling guideline to derive local process models from a given choreography; their operational semantics allows to correctly enact the entire choreography from the derived models only including the exchange of data. Targeting on successful interactions, we discuss means to ensure correct process choreography modeling. Finally, we implemented our approach by extending the camunda BPM platform with our approach and show its feasibility by realizing all service interaction patterns using only model-based concepts. (C) 2015 Elsevier Ltd. All rights reserved.},
  language  = {en}
}